Driving Intention Estimation Using Imaginary Drivers
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Solution Overview
Problem
Existing driving intention estimation systems are unreliable when detecting the relationship between a vehicle and lane markers is lost, as they fail to maintain accurate estimation in varying environments and with different drivers, leading to inconsistent eye movement interpretations.
Innovation Solution
A system that uses a combination of environmental information types to estimate driving intentions by calculating imaginary operations for multiple driver types, selecting the appropriate type based on detected conditions, and adjusting thresholds for accurate lane-change intention estimation, even when lane markers are not detected.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If driving intention is estimated using eye directions and frequency distribution, then the system can provide driving intention estimation, but the estimation accuracy varies with different running environments and different drivers
Solution Approach 1:
The patent segments the driving intention estimation into two independent parts: eye direction analysis and lane marker-based analysis. By dividing the estimation system into multiple independent analysis paths, the system can select the most reliable path based on current environmental conditions and driver characteristics, thereby improving overall reliability while adapting to different scenarios.
Solution Approach 2:
The patent creates a universal estimation system that functions through multiple methods (eye direction, lane marker detection, vehicle operation patterns). This multi-functional approach allows the system to adapt to different running environments and driver types by switching between or combining different estimation methods, resolving the contradiction between reliability and adaptability.
2Adaptability or versatility
If driving intention is estimated using lane marker information, then the system can avoid relying on driver-specific eye movements, but the estimation becomes unreliable when lane marker detection is lost or information is unreliable
Solution Approach 1:
The patent introduces a selection mechanism that acts as an intermediary between different estimation methods. This mediator evaluates the reliability of lane marker detection and eye direction data, then selects the most reliable method for current conditions. When lane markers are undetectable, the system switches to alternative methods, maintaining reliability while preserving the consistency benefits of lane marker-based estimation when available.
Solution Approach 2:
The system dynamically changes operational parameters by switching between different estimation methods based on environmental conditions. When lane marker detection reliability changes (e.g., from high to low due to weather or road conditions), the system adjusts by transitioning to alternative parameters such as eye direction analysis or vehicle operation pattern recognition, thereby maintaining consistent performance across different driver types and conditions.
3Reliability
If the system switches between different imaginary driver types based on environmental information, then the system can maintain accurate estimation in varying conditions, but the system complexity increases
Solution Approach 1:
The patent implements a dynamic selection mechanism that automatically chooses between different imaginary driver types based on real-time environmental information reliability. Rather than maintaining fixed complex structures for all conditions, the system dynamically adjusts which estimation model is active, achieving high reliability across varying environments while managing complexity through conditional activation rather than permanent structural complexity.
Data Source
AI summary
A driving intention estimation, driver assistance and vehicle with the driver assistance for providing a stable estimation of a driver's driving intention even if detection of a relationship between an own vehicle and lane markers is lost. A plurality of imaginary drivers of a first type and a second type, each being given a respective driving intention, are provided. When detection of lane markers is reliably kept, a driving intention by a real driver is estimated based on a comparison between an operation of the real driver to operations of the imaginary drivers of the first type that are calculated based on the relative positional relationship of the own vehicle to the detected lane marker. When the detection of lane markers is lost, operations of the plurality of imaginary drivers are calculated based on the relative positional relationship of the own vehicle to a preceding vehicle. In response to the status of detection of the lane marker, either the imaginary drivers of the first type or the second type are selected.